Visualização de Dados
Propósitos de Visualização dados: gapminder
Nathália Demetrio
source("https://raw.githubusercontent.com/traffordDataLab/assets/601e80334e0d78dfe913685561196b8b6fc278a7/theme/ggplot2/theme_lab.R")
theme_nath <- function () {
theme_grey(base_size = 11.5, base_family = "Roboto") %+replace%
theme(
# add padding to the plot
plot.margin = unit(rep(0.5, 4), "cm"),
# remove the plot background and border
plot.background = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
# make the legend and strip background transparent
legend.background = element_rect(fill = "transparent", colour = NA),
legend.key = element_rect(fill = "transparent", colour = NA),
strip.background = element_rect(fill = "transparent", colour = NA),
# add light, dotted major grid lines only
panel.grid.major = element_line(linetype = "dotted", colour = "#757575", size = 0.3),
panel.grid.minor = element_blank(),
# remove the axis tick marks and hide axis lines
axis.ticks = element_blank(),
axis.line = element_line(color = "#FFFFFF", size = 0.3),
# modify the bottom margins of the title and subtitle
plot.title = element_text(size = 18, colour = "#757575", hjust = 0, margin = margin(b = 4)),
plot.subtitle = element_text(size = 12, colour = "#757575", hjust = 0, margin = margin(b = 10)),
# add padding to the caption
plot.caption = element_text(size = 10, colour = "#757575", hjust = 1, margin = margin(t = 15)),
# change to Open Sans for axes titles, tick labels, legend title and legend key, and strip text
axis.title = element_text(family = "Open Sans", size = 11, colour = "#757575", face = "plain", hjust = 1),
axis.text = element_text(family = "Open Sans", size = 10, colour = "#757575", face = "plain"),
legend.title = element_text(size = 12, colour = "#757575"),
legend.text = element_text(size = 10, colour = "#757575"),
strip.text = element_text(family = "Open Sans", size = 12, colour = "#757575", face = "plain")
)
}
#lista de cores da paleta
#Set2 = c("#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3")library(tidyverse)
library(patchwork)Introdução
Este arquivo concentra as visualizações relacionadas aos dados do gapminder.
Dados
Serão utilizados dados da iniciativa gapminder, disponibilizada em gapminder::gapminder e dslabs::gapminder, tendo que neste último algumas informações a mais são disponibilizadas.
dslabs
Esta base possui vários anos a mais que a base original, além da
informação de region, mais países, e as features
infant_mortality e fertility. Contudo os
valores das variáveis: population, gdp e life_expectancy, infos que
também constam na base orginal do gapminder, possuem valores
razoavelmente distintos (da base original, e um pouco distoantes dentro
do próprio histórico).
No mais, após o merge com as bases originais, o
infant_mortality particularmente apresenta muitos NAs, bem
como o gdp.
dslabs <- dslabs::gapminder %>%
#anos da base gapminder::gapminder
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977,
1982, 1987, 1992, 1997, 2002, 2007)) %>%
select(-life_expectancy, -population, -gdp) %>%
glimpse()## Rows: 1,850
## Columns: 6
## $ country <fct> "Albania", "Algeria", "Angola", "Antigua and Barbuda"…
## $ year <int> 1962, 1962, 1962, 1962, 1962, 1962, 1962, 1962, 1962,…
## $ infant_mortality <dbl> 106.50, 148.20, NA, NA, 59.59, NA, NA, 19.50, 32.90, …
## $ fertility <dbl> 5.96, 7.65, 7.39, 4.34, 3.09, 4.44, 4.47, 3.43, 2.80,…
## $ continent <fct> Europe, Africa, Africa, Americas, Americas, Asia, Ame…
## $ region <fct> Southern Europe, Northern Africa, Middle Africa, Cari…gapminder
A base gapminder tratada tem um total de 142 países para cada um dos anos, com 12 anos distintos, entre 1952 e 2007 .
gapminder <- gapminder::gapminder %>%
left_join(gapminder::country_codes) %>%
left_join(dslabs) %>%
mutate(region = case_when(
country == "Afghanistan" ~ "Central Asia",
country == "Korea, Dem. Rep." ~ "Eastern Asia",
country == "Korea, Rep." ~ "Eastern Asia",
country == "Myanmar" ~ "Southeast Asia",
country == "Reunion" ~ "Eastern Africa",
country == "Sao Tome and Principe" ~ "Central Africa",
country == "Somalia" ~ "Eastern Africa",
country == "Taiwan" ~ "Eastern Asia",
country == "Turkey" ~ "Western Asia",
country == "Yemen, Rep." ~ "Western Asia",
TRUE ~ region)) %>%
janitor::clean_names() %>%
mutate(continent = recode(continent,
"Asia" = "Ásia",
"Europe" = "Europa",
"Africa" = "África",
"Americas" = "América",
"Oceania" = "Oceania")) %>%
relocate(region, .after = continent) %>%
glimpse()## Rows: 1,704
## Columns: 11
## $ country <chr> "Afghanistan", "Afghanistan", "Afghanistan", "Afghani…
## $ continent <fct> Ásia, Ásia, Ásia, Ásia, Ásia, Ásia, Ásia, Ásia, Ásia,…
## $ region <chr> "Central Asia", "Central Asia", "Central Asia", "Cent…
## $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992,…
## $ life_exp <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.85…
## $ pop <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880…
## $ gdp_percap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786…
## $ iso_alpha <chr> "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG…
## $ iso_num <int> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 8, 8, 8, 8, 8, 8,…
## $ infant_mortality <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ fertility <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… #código complementar para identificar países sem região atribuída:
#gapminder %>% filter(is.na(region)) %>% select(country, continent, region) %>% unique() gapminder_full (data frame que será utilizado)
Já a base gapminder_full, tem variedade no números de países para 58
anos distintos, entre 1950 e
max(gapminder::gapminder_unfiltered$year). O ano com a
maior quantidade de países é 2002, com 183 países
gapminder_full <- gapminder::gapminder_unfiltered %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002, 2007)) %>%
left_join(gapminder::country_codes) %>%
left_join(dslabs) %>%
mutate(region = case_when(
country == "Afghanistan" ~ "Central Asia",
country == "Korea, Dem. Rep." ~ "Eastern Asia",
country == "Korea, Rep." ~ "Eastern Asia",
country == "Myanmar" ~ "Southeast Asia",
country == "Reunion" ~ "Eastern Africa",
country == "Sao Tome and Principe" ~ "Central Africa",
country == "Somalia" ~ "Eastern Africa",
country == "Taiwan" ~ "Eastern Asia",
country == "Turkey" ~ "Western Asia",
country == "Yemen, Rep." ~ "Western Asia",
TRUE ~ region)) %>%
mutate(region = case_when(
country == "Cyprus" ~ "Western Asia",
country == "French Guiana" ~ "South America",
country == "Guadeloupe" ~ "Caribbean",
country == "Martinique" ~ "Caribbean",
country == "Netherlands Antilles" ~ "South America",
TRUE ~ region)) %>%
janitor::clean_names() %>%
mutate(continent = recode(continent,
"Asia" = "Ásia",
"Europe" = "Europa",
"Africa" = "África",
"Americas" = "América",
"Oceania" = "Oceania")) %>%
relocate(region, .after = continent) %>%
glimpse()## Rows: 2,013
## Columns: 11
## $ country <chr> "Afghanistan", "Afghanistan", "Afghanistan", "Afghani…
## $ continent <fct> Ásia, Ásia, Ásia, Ásia, Ásia, Ásia, Ásia, Ásia, Ásia,…
## $ region <chr> "Central Asia", "Central Asia", "Central Asia", "Cent…
## $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992,…
## $ life_exp <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.85…
## $ pop <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880…
## $ gdp_percap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786…
## $ iso_alpha <chr> "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG…
## $ iso_num <int> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 8, 8, 8, 8, 8, 8,…
## $ infant_mortality <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ fertility <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…view
gapminder_full %>% DT::datatable()Magnitude
Este capítulo se baseia nas análises feitas pelo @traffordDataLab
Qtd países por continente
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2002") %>%
group_by(continent) %>%
count() %>%
ggplot(aes(x = continent, y = n, fill = continent), color = "white") +
geom_col(alpha = 0.8) +
geom_text(aes(label = n), vjust = -0.5, size = 4, colour = "#757575") +
geom_hline(yintercept=0, color = "lightgrey") +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, ano de 2002",
caption = "Fonte: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
#panel.grid = element_blank(),
axis.text.y=element_blank(),
legend.position = "none") 
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2002") %>%
group_by(continent) %>%
count() %>%
ggplot(aes(x = continent, y = n, fill = continent), color = "white") +
geom_col(alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, ano de 2002",
caption = "Fonte: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
#panel.grid.major.y = element_blank(),
#panel.grid = element_blank(),
#axis.text.y=element_blank(),
legend.position = "none") 
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2002") %>%
group_by(continent) %>%
count() %>%
ggplot(aes(x = continent, y = n, fill = continent), color = "white") +
geom_col(alpha = 0.8) +
geom_text(aes(label = n), vjust = -0.5, size = 4, colour = "#757575") +
geom_hline(yintercept=0, color = "lightgrey") +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, ano de 2002",
caption = "Fonte: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
#panel.grid.major.y = element_blank(),
#panel.grid = element_blank(),
#axis.text.y=element_blank(),
legend.position = "none") 
Life_exp
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2002") %>%
group_by(continent) %>%
summarise(life_exp = mean(life_exp)) %>%
ggplot(aes(x = continent, y = life_exp, fill = continent)) +
geom_col(fill = "#FFD92F", alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
labs(title = "",
subtitle = "Média Expectativa de Vida por Continente, ano de 2002",
caption = "Fonte: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2002") %>%
group_by(continent) %>%
summarise(life_exp = mean(life_exp)) %>%
ggplot(aes(x = continent, y = life_exp, fill = continent)) +
geom_col(alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Média Expectativa de Vida por Continente, ano de 2002",
caption = "Fonte: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
Comparação
absoluta
agrupado
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 2002)) %>%
group_by(year, continent) %>%
count() %>%
ggplot(aes(x = year, y = n, group = continent, fill = continent)) +
geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_x_continuous(breaks = c(1952, 2002), expand = c(0, 0)) +
scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, comparação por período",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
legend.position = "bottom")
gapminder_full ## # A tibble: 2,013 × 11
## country continent region year life_exp pop gdp_percap iso_alpha iso_num
## <chr> <fct> <chr> <int> <dbl> <int> <dbl> <chr> <int>
## 1 Afghanis… Ásia Centr… 1952 28.8 8.43e6 779. AFG 4
## 2 Afghanis… Ásia Centr… 1957 30.3 9.24e6 821. AFG 4
## 3 Afghanis… Ásia Centr… 1962 32.0 1.03e7 853. AFG 4
## 4 Afghanis… Ásia Centr… 1967 34.0 1.15e7 836. AFG 4
## 5 Afghanis… Ásia Centr… 1972 36.1 1.31e7 740. AFG 4
## 6 Afghanis… Ásia Centr… 1977 38.4 1.49e7 786. AFG 4
## 7 Afghanis… Ásia Centr… 1982 39.9 1.29e7 978. AFG 4
## 8 Afghanis… Ásia Centr… 1987 40.8 1.39e7 852. AFG 4
## 9 Afghanis… Ásia Centr… 1992 41.7 1.63e7 649. AFG 4
## 10 Afghanis… Ásia Centr… 1997 41.8 2.22e7 635. AFG 4
## # ℹ 2,003 more rows
## # ℹ 2 more variables: infant_mortality <dbl>, fertility <dbl>gapminder::gapminder_unfiltered %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 2002)) %>%
group_by(year, continent) %>%
count() %>%
mutate(year = as.character(year)) %>%
ggplot(aes(x = continent, y = n, group = year, fill = continent)) +
geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, comparação por período: 1952 vs. 2002",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL, y = NULL, fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
legend.position = "bottom")
gapminder_full ## # A tibble: 2,013 × 11
## country continent region year life_exp pop gdp_percap iso_alpha iso_num
## <chr> <fct> <chr> <int> <dbl> <int> <dbl> <chr> <int>
## 1 Afghanis… Ásia Centr… 1952 28.8 8.43e6 779. AFG 4
## 2 Afghanis… Ásia Centr… 1957 30.3 9.24e6 821. AFG 4
## 3 Afghanis… Ásia Centr… 1962 32.0 1.03e7 853. AFG 4
## 4 Afghanis… Ásia Centr… 1967 34.0 1.15e7 836. AFG 4
## 5 Afghanis… Ásia Centr… 1972 36.1 1.31e7 740. AFG 4
## 6 Afghanis… Ásia Centr… 1977 38.4 1.49e7 786. AFG 4
## 7 Afghanis… Ásia Centr… 1982 39.9 1.29e7 978. AFG 4
## 8 Afghanis… Ásia Centr… 1987 40.8 1.39e7 852. AFG 4
## 9 Afghanis… Ásia Centr… 1992 41.7 1.63e7 649. AFG 4
## 10 Afghanis… Ásia Centr… 1997 41.8 2.22e7 635. AFG 4
## # ℹ 2,003 more rows
## # ℹ 2 more variables: infant_mortality <dbl>, fertility <dbl>gapminder::gapminder_unfiltered %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 2002)) %>%
group_by(year, continent) %>%
count() %>%
mutate(year = as.character(year)) %>%
ggplot(aes(x = continent, y = n, group = year,
fill = interaction(year, continent))) +
geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_fill_manual(values = c("#66C2A5", "#388C72", "#FC8D62", "#FA4F0A",
"#8DA0CB","#4964A1", "#E78AC3","#D42C94",
"#A6D854", "#77A927")) +
labs(title = "",
subtitle = "Contagem de Países por Continente, comparação por período: 1952 vs. 2002",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL, y = NULL, fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
(p1 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
#filter(year %in% c(1952, 1977, 2002)) %>%
group_by(year, continent) %>%
count() %>%
ggplot(aes(x = year, y = n, group = continent, fill = continent)) +
geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
#scale_x_continuous(breaks = c(1952, 1977, 2002), expand = c(0, 0)) +
scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, comparação por período",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
legend.position = "bottom"))
agrupado + continent by years
(p0 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
#filter(year %in% c(1952, 1977, 2002)) %>%
group_by(year, continent) %>%
count() %>%
ggplot(aes(x = year, y = n, group = continent, fill = continent)) +
geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
facet_wrap(. ~ continent) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, comparação por período",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(0, 60)) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none"))
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
#filter(year %in% c(1952, 1977, 2002)) %>%
group_by(year, continent) %>%
count() %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = continent, y = n, group = year, fill = year)) +
geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#facet_grid(. ~ year, scales = "free_x") +
scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Contagem de Países por Continente, de 1952 a 2002",
caption = "Source: Gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "bottom")
absoluta e relativa não normalizada
(p2 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
#filter(year %in% c(1952, 1977, 2002)) %>%
group_by(year, continent) %>%
count() %>%
ggplot(aes(x = year, y = n, fill = continent)) +
geom_col(colour = "white", size = 0.2, alpha = 0.8) +
geom_hline(yintercept=0, color = "lightgrey") +
scale_x_continuous(breaks = c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002),
expand = c(0, 0)) +
scale_fill_brewer(palette = "Set2") +
guides(fill = guide_legend(reverse = F)) +
labs(title = "",
subtitle = "Proporção da contagem de países por continente, comparação por período",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "right"))
relativa
(p3 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
#filter(year %in% c(1952, 1977, 2002)) %>%
group_by(year, continent) %>%
count() %>%
ggplot(aes(x = year, y = n, fill = continent)) +
geom_col(position = "fill", colour = "white", size = 0.2, alpha = 0.8) +
scale_x_continuous(breaks = c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002), expand = c(0, 0)) +
scale_y_continuous(labels = scales::percent, expand = c(0, 0)) +
scale_fill_brewer(palette = "Set2") +
guides(fill = guide_legend(reverse = F)) +
labs(title = "",
subtitle = "Proporção da contagem de países por continente, comparação por período",
caption = "Source: gapminder.org | @traffordDataLab",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
geom_hline(yintercept=0, color = "lightgrey") +
theme(panel.grid.major.x = element_blank(),
legend.position = "right"))
clean versions
#patchwork::
(p11 <- p1 +
theme(legend.position = "none") +
labs(subtitle = "",
caption = ""))(p22 <- p2 +
theme(legend.position = "none") +
labs(subtitle = "",
caption = ""))(p33 <- p3 +
theme(legend.position = "none") +
labs(subtitle = "",
caption = "") )
(p11 / p22 / p33)Relação
fertility x life_exp (2007)
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, color = year, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.6) +
viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
plotly::ggplotly(p)temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year))
(p <- temp %>%
ggplot(aes(x = fertility, y = life_exp, color = year, label = country)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.1) +
geom_point(data = . %>% filter(country == "Japan"),
shape=16, size = 2, stroke = 0, color = "#21918c") +
ggrepel::geom_label_repel(data = . %>% filter(country == "Japan"),
color = "#21918c",
max.overlaps = 50,
nudge_x = -.3, nudge_y = 3,
segment.curvature = 0.5) +
scale_color_manual(values = c("#440154")) +
labs(title = "",
subtitle = "Expectativa de Vida vs. Fertilidade",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
mutate(year = as_factor(year))
(p <- temp %>%
ggplot(aes(x = fertility, y = life_exp, color = year, label = country)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.1) +
geom_point(data = . %>% filter(country == "Japan"),
shape=16, size = 2, stroke = 0, color = "#21918c") +
ggrepel::geom_label_repel(data = . %>% filter(country == "Japan"),
color = "#21918c",
max.overlaps = 50,
nudge_x = -.3, nudge_y = 3,
segment.curvature = 0.5) +
geom_point(data = . %>% filter(country == "China"),
shape=16, size = 2, stroke = 0, color = "#21918c") +
ggrepel::geom_label_repel(data = . %>% filter(country == "China"),
color = "#21918c",
max.overlaps = 50,
nudge_x = -.1, nudge_y = -1.5,
box.padding = 1,
segment.curvature = 0.5) +
scale_color_manual(values = c("#440154")) +
labs(title = "",
subtitle = "Expectativa de Vida vs. Fertilidade",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year))
(p <- temp %>%
ggplot(aes(x = fertility, y = life_exp, color = year, label = country)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.1) +
# geom_point(data = . %>% filter(life_exp == max(life_exp)),
# color = "#21918c") +
# ggrepel::geom_label_repel(data = . %>%
# filter(life_exp >70, fertility >3, fertility <4),
# color = "#21918c",
# max.overlaps = 50,
# nudge_x = -.3, nudge_y = 3,
# segment.curvature = 0.9) +
geom_point(data = . %>% filter(country == "Syria"),
shape=16, size = 2, stroke = 0, color = "#21918c") +
ggrepel::geom_label_repel(data = . %>% filter(country == "Syria"),
color = "#21918c",
max.overlaps = 50,
nudge_x = .3, nudge_y = 3,
box.padding = 1,
segment.curvature = 0.9) +
geom_point(data = . %>% filter(country == "Japan"),
shape=16, size = 2, stroke = 0, color = "#21918c") +
ggrepel::geom_label_repel(data = . %>% filter(country == "Japan"),
color = "#21918c",
max.overlaps = 50,
nudge_x = -.3, nudge_y = 3,
segment.curvature = 0.5) +
geom_point(data = . %>% filter(country == "China"),
shape=16, size = 2, stroke = 0, color = "#21918c") +
ggrepel::geom_label_repel(data = . %>% filter(country == "China"),
color = "#21918c",
max.overlaps = 50,
nudge_x = -.1, nudge_y = -1.5,
box.padding = 1,
segment.curvature = 0.5) +
scale_color_manual(values = c("#440154")) +
labs(title = "",
subtitle = "Expectativa de Vida vs. Fertilidade",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, color = year, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.6) +
geom_smooth(method = "lm") +
viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, color = year, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.6) +
geom_smooth() +
viridis::scale_color_viridis(discrete = T, direction = 1) +
#scale_color_manual(values = c('#9ccb86','#cf597e', '#009392','#eeb479' )) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
overplotting
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.6, color = "#440154") +
#viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade, 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.6, color = "#440154") +
#viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade, de 1952 a 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.4, color = "#440154") +
#viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade, de 1952 a 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 0.3, color = "#440154") +
#viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade, de 1952 a 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year %in% c("2007")) %>%
#filter(continent == "Europa") %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, label = country)) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
geom_point(shape=16, size = 2, stroke = 0, alpha = 1, color = "#440154") +
#viridis::scale_color_viridis(discrete = T, direction = 1) +
labs(title = "",
#subtitle = "Expectativa de Vida vs. Fertilidade, comparação por período",
subtitle = "Expectativa de Vida vs. Fertilidade, de 1952 a 2007",
# caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(1, 8), minor_breaks = seq(1, 8, 1), n.breaks = 8) +
scale_y_continuous(limits = c(30, 87)) +
theme(#panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right"))
colorBlindness::cvdPlot(p)
continents
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
filter(year == "2007") %>%
#filter(continent == "Oceania") %>%
group_by(year, country, continent) %>%
summarise(
life_exp = mean(life_exp, na.rm=T),
fertility = mean(fertility, na.rm=T)
) %>%
ungroup() %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = fertility, y = life_exp, color = continent)) +
#ggplot(aes(x = continent, y = n, group = year, fill = year)) +
#geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
#geom_text(aes(label = country), vjust = "inward") +
geom_point() +
geom_smooth(method = "glm") +
facet_grid(. ~ continent, scales = "free_x") +
scale_color_brewer(palette = "Set2") +
# labs(title = "",
# subtitle = "Contagem de Países por Continente, de 1952 a 2002",
# caption = "Source: Gapminder.org",
# x = NULL,
# y = NULL,
# fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none"))
# plotly::ggplotly(p)gdp_percap x life_exp
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
filter(year == "2002") %>%
#filter(continent == "Oceania") %>%
# group_by(year, country, continent) %>%
# summarise(
# life_exp = mean(life_exp, na.rm=T),
# fertility = mean(fertility, na.rm=T)
# ) %>%
# ungroup() %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = gdp_percap, y = life_exp, color = continent)) +
#ggplot(aes(x = continent, y = n, group = year, fill = year)) +
#geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
#stat_summary(geom="point", fun.data = ~mean(.x,na.rm=T)) +
#geom_text(aes(label = country), vjust = "inward") +
geom_point() +
#geom_smooth(method = "glm") +
scale_color_brewer(palette = "Set2") +
# labs(title = "",
# subtitle = "Contagem de Países por Continente, de 1952 a 2002",
# caption = "Source: Gapminder.org",
# x = NULL,
# y = NULL,
# fill = NULL) +
#scale_x_log10(labels = scales::dollar) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none"))
# plotly::ggplotly(p)( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
filter(year == "2002") %>%
#filter(continent == "Oceania") %>%
# group_by(year, country, continent) %>%
# summarise(
# life_exp = mean(life_exp, na.rm=T),
# fertility = mean(fertility, na.rm=T)
# ) %>%
# ungroup() %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = gdp_percap, y = life_exp, color = continent)) +
#ggplot(aes(x = continent, y = n, group = year, fill = year)) +
#geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
#stat_summary(geom="point", fun.data = ~mean(.x,na.rm=T)) +
#geom_text(aes(label = country), vjust = "inward") +
geom_point(aes(size = pop)) +
#geom_smooth(method = "glm") +
scale_color_brewer(palette = "Set2") +
# labs(title = "",
# subtitle = "Contagem de Países por Continente, de 1952 a 2002",
# caption = "Source: Gapminder.org",
# x = NULL,
# y = NULL,
# fill = NULL) +
#scale_x_log10(labels = scales::dollar) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none"))
# plotly::ggplotly(p)( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
filter(year == "2002") %>%
#filter(continent == "Oceania") %>%
# group_by(year, country, continent) %>%
# summarise(
# life_exp = mean(life_exp, na.rm=T),
# fertility = mean(fertility, na.rm=T)
# ) %>%
# ungroup() %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = gdp_percap, y = life_exp, color = continent)) +
#ggplot(aes(x = continent, y = n, group = year, fill = year)) +
#geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
#stat_summary(geom="point", fun.data = ~mean(.x,na.rm=T)) +
#geom_text(aes(label = country), vjust = "inward") +
geom_point() +
#geom_smooth(method = "glm") +
facet_grid(. ~ continent, scales = "free_x") +
scale_color_brewer(palette = "Set2") +
# labs(title = "",
# subtitle = "Contagem de Países por Continente, de 1952 a 2002",
# caption = "Source: Gapminder.org",
# x = NULL,
# y = NULL,
# fill = NULL) +
#scale_x_log10(labels = scales::dollar) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none"))
# plotly::ggplotly(p)( p <- gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
filter(year == "2007") %>%
filter(continent == "Europa") %>%
# group_by(year, country, continent) %>%
# summarise(
# life_exp = mean(life_exp, na.rm=T),
# fertility = mean(fertility, na.rm=T)
# ) %>%
# ungroup() %>%
mutate(year = as_factor(year)) %>%
ggplot(aes(x = gdp_percap, y = life_exp, color = continent)) +
#ggplot(aes(x = continent, y = n, group = year, fill = year)) +
#geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
#stat_summary(geom="point", fun.data = ~mean(.x,na.rm=T)) +
#geom_text(aes(label = country), vjust = "inward") +
geom_point() +
#geom_smooth(method = "glm") +
facet_grid(. ~ continent, scales = "free_x") +
scale_color_brewer(palette = "Set2") +
# labs(title = "",
# subtitle = "Contagem de Países por Continente, de 1952 a 2002",
# caption = "Source: Gapminder.org",
# x = NULL,
# y = NULL,
# fill = NULL) +
scale_x_continuous(labels = scales::dollar) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none"))
# plotly::ggplotly(p)Evolução
fertility
gapminder_full %>%
filter(continent != "FSU") %>%
#filter(year == "2007") %>%
group_by(continent, year) %>%
summarise(
NA_fertility = sum(is.na(fertility)),
mean_fertility = mean(fertility, na.rm = T),
) %>%
ggplot(aes(x = year, y = mean_fertility, color = continent)) +
#geom_point(color = "gray") +
#geom_line(aes(group = country), color = "gray") +
# geom_point(alpha = 0.3) +
geom_line() +
ggrepel::geom_label_repel(data = . %>% filter(year == 1962), aes(label = continent)) +
scale_colour_brewer(palette = "Set2") +
guides(fill = guide_legend(reverse = F)) +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
life_exp
line
continent
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
# mutate(year = lubridate::year(lubridate::as_date(year))) %>%
mutate(year = as.integer(year)) %>%
ggplot(aes(x = year, y = life_exp)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(color = "#440154", size = 0.8) +
#geom_point(color = "#440154") +
#ggrepel::geom_label_repel(data = . %>% filter(year == 1962), aes(label = continent)) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
#scale_x_date(date_breaks = "1 year") +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
#panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
# mutate(year = lubridate::year(lubridate::as_date(year))) %>%
mutate(year = as.integer(year)) %>%
ggplot(aes(x = year, y = life_exp)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(color = "#440154", size = 0.8) +
geom_point(color = "#440154") +
#ggrepel::geom_label_repel(data = . %>% filter(year == 1962), aes(label = continent)) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
#scale_x_date(date_breaks = "1 year") +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
#panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
# mutate(year = lubridate::year(lubridate::as_date(year))) %>%
mutate(year = as.integer(year)) %>%
ggplot(aes(x = year, y = life_exp)) +
geom_hline(yintercept=40, color = "lightgrey") +
#geom_line(color = "#440154", size = 0.8) +
geom_point(color = "#440154") +
#ggrepel::geom_label_repel(data = . %>% filter(year == 1962), aes(label = continent)) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
#scale_x_date(date_breaks = "1 year") +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
#panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year)) %>%
ggplot(aes(x = year, y = life_exp)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(color = "#440154", size = 0.8) +
#geom_point(color = "#440154") +
ggrepel::geom_text_repel(data = . %>% filter(year == min(year)),
aes(label = round(life_exp,0)),
color = "#440154", nudge_x = -1) +
ggrepel::geom_text_repel(data = . %>% filter(year == max(year)),
aes(label = round(life_exp,0)),
color = "#440154", nudge_x = 1) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year)) %>%
ggplot(aes(x = year, y = life_exp)) +
geom_vline(xintercept=1987, color = "lightgrey", linetype =2) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(color = "#440154", size = 0.8) +
#geom_point(color = "#440154") +
ggrepel::geom_text_repel(data = . %>% filter(year == min(year)),
aes(label = round(life_exp,0)),
color = "#440154", nudge_x = -1) +
ggrepel::geom_text_repel(data = . %>% filter(year == max(year)),
aes(label = round(life_exp,0)),
color = "#440154", nudge_x = 1) +
ggrepel::geom_text_repel(data = . %>% filter(year == 1987),
aes(label = round(life_exp,0)),
color = "#440154", nudge_y = 1) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_brewer(palette = "Set2") +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp_new <- temp %>%
filter(year == max(year)) %>%
distinct(continent, life_exp)
legend_ord <- rev(levels(with(temp_new, reorder(continent, life_exp))))
temp %>%
mutate(continent = as_factor(continent)) %>%
mutate(continent = forcats::fct_relevel(continent,
c( "FSU", "Europa", "América", "Oceania","Ásia","África"))) %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_manual(
values = c("#E78AC3","#FC8D62", "#A6D854", "#8DA0CB","#66C2A5")) +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "right")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp_new <- temp %>%
filter(year == max(year)) %>%
distinct(continent, life_exp)
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
geom_point() +
labs(title = "",
subtitle = "Evolução da Expectativa de Vida, média de todos os países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_brewer(palette = "Set2") +
scale_y_continuous(limits = c(40, 80),
sec.axis = dup_axis(
breaks = temp_new$life_exp,
labels = temp_new$continent,
name = NULL)
) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
ggrepel::geom_text_repel(data = . %>% filter(year == 1962), aes(label = continent),
vjust = 1, hjust = 0.1) +
labs(title = "",
subtitle = "Evolução da Expectativa de Vida, por continente",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_brewer(palette = "Set2") +
scale_y_continuous(limits = c(40, 80), guide = guide_axis(position = 'right')) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
ggrepel::geom_label_repel(data = . %>% filter(year == 1992), aes(label = continent)) +
# ggrepel::geom_text_repel(data = . %>% filter(year == max(year)),
# aes(label = round(life_exp,0)),nudge_x = 1) +
# ggrepel::geom_text_repel(data = . %>% filter(year == min(year)),
# aes(label = round(life_exp,0)), nudge_x = -1) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_brewer(palette = "Set2") +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
#axis.text.y=element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
ggrepel::geom_label_repel(data = . %>% filter(year == 1992), aes(label = continent)) +
# ggrepel::geom_text_repel(data = . %>% filter(year == max(year)),
# aes(label = round(life_exp,0)),nudge_x = 1) +
# ggrepel::geom_text_repel(data = . %>% filter(year == min(year)),
# aes(label = round(life_exp,0)), nudge_x = -1) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_brewer(palette = "Set2") +
scale_y_continuous(limits = c(40, 80), guide = guide_axis(position = 'right')) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
#axis.text.y=element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
mutate(year = as.integer(year))
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(size = 0.8) +
ggrepel::geom_label_repel(data = . %>% filter(year == 1992), aes(label = continent)) +
ggrepel::geom_text_repel(data = . %>% filter(year == max(year)),
aes(label = round(life_exp,0)),nudge_x = 1) +
ggrepel::geom_text_repel(data = . %>% filter(year == min(year)),
aes(label = round(life_exp,0)), nudge_x = -1) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_color_brewer(palette = "Set2") +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(continent, year) %>%
summarise(
NA_fertility = sum(is.na(life_exp)),
life_exp = mean(life_exp, na.rm = T),
) %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
#geom_point(color = "gray") +
#geom_line(aes(group = country), color = "gray") +
# geom_point(alpha = 0.3) +
geom_line(size = 0.8) +
ggrepel::geom_label_repel(data = . %>% filter(year == 1962), aes(label = continent)) +
scale_colour_brewer(palette = "Set2") +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80), guide = guide_axis(position = 'right')) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
ggplot(aes(x = year, y = life_exp)) +
scale_color_manual(values = c("#440154")) +
geom_point(alpha = 0.3, color="lightgrey") +
geom_line(aes(group = country), alpha = 0.3, color="lightgrey") +
geom_smooth(color = "#440154") +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year >= 1962, year <= 2007) %>%
group_by(year) %>%
summarise(
life_exp = mean(life_exp, na.rm = T),
) %>%
# mutate(year = lubridate::year(lubridate::as_date(year))) %>%
mutate(year = as.integer(year))
temp2 <- tibble(
year = c(2007, 2008, 2009, 2010),
life_exp = c(67.8, 68, 68.2, 68.6),
upper_bound = c(68.1,68.5,69.2,70),
lower_bound = c(67.5,67.5,67,67.1))
temp %>%
ggplot(aes(x = year, y = life_exp)) +
geom_hline(yintercept=40, color = "lightgrey") +
geom_line(color = "#440154", size = 0.8) +
#geom_point(color = "#440154") +
#ggrepel::geom_label_repel(data = . %>% filter(year == 1962), aes(label = continent)) +
geom_smooth(data=temp2, aes(x = year, y = life_exp, ymax=upper_bound, ymin=lower_bound),
colour='#cf4446', stat='identity', linetype = "twodash") +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos países",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
#scale_x_date(date_breaks = "1 year") +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
#panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
facet/ grouping
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
# filter(continent %in% c("América")) %>%
filter(year >= 1962, year <= 2007)
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(alpha = 0.3, color="lightgrey", size = .5) +
geom_line(aes(group = country), alpha = 0.3, color="lightgrey") +
geom_smooth() +
scale_colour_brewer(palette = "Set2") +
facet_wrap(continent ~ .) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1965, 2010), n.breaks = 4) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
# filter(continent %in% c("América")) %>%
filter(year >= 1962, year <= 2007)
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(alpha = 0.3, color="lightgrey", size = .5) +
geom_line(aes(group = country), alpha = 0.3, color="lightgrey") +
geom_smooth() +
scale_colour_brewer(palette = "Set2") +
#facet_wrap(continent ~ .) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1965, 2010), n.breaks = 4) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
# filter(continent %in% c("América")) %>%
filter(year >= 1962, year <= 2007)
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(size = .5, alpha = 0.6) +
geom_line(aes(group = country), alpha = 0.6) +
#geom_smooth() +
scale_colour_brewer(palette = "Set2") +
facet_wrap(continent ~ .) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1965, 2010), n.breaks = 4) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
# filter(continent %in% c("América")) %>%
filter(year >= 1962, year <= 2007)
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(alpha = 0.6, size = .5) +
geom_line(aes(group = country), alpha = 0.6) +
#geom_smooth() +
scale_colour_brewer(palette = "Set2") +
#facet_wrap(continent ~ .) +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média dos continentes",
#caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1965, 2010), n.breaks = 4) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none")
temp <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(continent %in% c("América")) %>%
filter(year >= 1962, year <= 2007)
temp %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
scale_color_manual(values = c("#FC8D62")) +
geom_point(alpha = 0.3, color="lightgrey") +
geom_line(aes(group = country), alpha = 0.3, color="lightgrey") +
geom_smooth() +
labs(title = "",
subtitle = "Evolução da expectativa de vida, média do continente Americano",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_y_continuous(limits = c(40, 80)) +
scale_x_continuous(limits = c(1960, 2010), n.breaks = 10) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
legend.position = "none")
line + variability (by countries)
gapminder %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
#geom_point(color = "gray") +
#geom_line(aes(group = country), color = "gray") +
geom_point(alpha = 0.3) +
geom_line(aes(group = country), alpha = 0.3) +
scale_colour_brewer(palette = "Set2") +
guides(fill = guide_legend(reverse = F)) +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank())
gapminder %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(alpha = 0.3, color = "lightgray") +
geom_line(aes(group = country), alpha = 0.3, color = "lightgray") +
geom_smooth() +
scale_colour_brewer(palette = "Set2") +
guides(fill = guide_legend(reverse = F)) +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank())
gapminder %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
#geom_point(color = "gray") +
#geom_line(aes(group = country), color = "gray") +
geom_point(alpha = 0.3) +
geom_line(aes(group = country), alpha = 0.3) +
geom_smooth() +
scale_colour_brewer(palette = "Set2") +
guides(fill = guide_legend(reverse = F)) +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank())
gapminder %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(alpha = 0.3, color="lightgrey") +
geom_line(aes(group = country), alpha = 0.3, color="lightgrey") +
geom_smooth() +
facet_grid( continent ~ .) +
scale_colour_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Evolução da Expectativa de Vida Média, por continente",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c(1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002)) %>%
ggplot(aes(x = year, y = life_exp, color = continent)) +
geom_point(alpha = 0.3) +
geom_line(aes(group = country), alpha = 0.3) +
geom_smooth() +
facet_grid( continent ~ .) +
scale_colour_brewer(palette = "Set2") +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
dot - 1962 vs. 2007
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(continent %in% c("América", "Ásia", "Europa")) %>%
filter(year %in% c("1962", "2007")) %>%
group_by(year, continent, region) %>%
summarise(
life_exp = mean(life_exp, na.rm=T)
) %>%
ungroup() %>%
mutate(year = as_factor(year)) %>%
mutate(color = paste(continent,"-", region,"-", year)) %>%
ggplot(aes(x = life_exp, y = region, color = color, label = year)) +
geom_line(aes(group = region), color = "lightgrey", size = 1.8, alpha = 0.3) +
geom_point() +
scale_color_manual(values =
c(rep(c("lightgrey", "#FC8D62"),4),
rep(c("lightgrey", "#8DA0CB"),6),
rep(c("lightgrey", "#E78AC3"),5))) +
#Set2 = c("#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3")
#scale_colour_brewer(palette = "Set2") +
facet_grid(continent ~ ., scales = "free", space = "free_y") +
labs(title = "",
subtitle = "...",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = .05),
#panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = .05),
#strip.text.y.left = element_text(angle = 0),
strip.text.y = element_text(angle = 0),
legend.position = "none")) 
( p <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(continent %in% c("América", "Ásia", "Europa")) %>%
filter(year %in% c("1962", "2007")) %>%
group_by(year, continent, region) %>%
summarise(
life_exp = mean(life_exp, na.rm=T)
) %>%
ungroup() %>%
mutate(year = as_factor(year)) %>%
mutate(color = paste(continent,"-", region,"-", year)) %>%
ggplot(aes(x = life_exp, y = region, label = year, shape = year)) +
geom_line(aes(group = region, color = continent), size = 1.8, alpha = 0.3) +
geom_point(data = . %>% filter(year == "2007"), aes(color = continent), size = 2) +
geom_point(data = . %>% filter(year == "1962"), aes(color = continent), alpha = .6) +
scale_color_manual(values = c("#FC8D62", "#8DA0CB", "#E78AC3")) +
#scale_color_manual(values = c("#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854")) +
#scale_colour_brewer(palette = "Set2") +
facet_grid(continent ~ ., scales = "free", space = "free_y") +
labs(title = "",
subtitle = "Evolução da Expectativa de Vida por subdivisões dos continentes",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
guides(color=FALSE) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = .05),
#panel.grid.minor = element_line(linetype = "dotted", colour = "lightgrey", size = .05),
#strip.text.y.left = element_text(angle = 0),
strip.text.y = element_text(angle = 0),
legend.position = "top")) 
Distribuição
Países
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("1962", "2007")) %>%
select(life_exp, year) %>%
group_by(year) %>%
skimr::skim()| Name | Piped data |
| Number of rows | 325 |
| Number of columns | 2 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | year |
Variable type: numeric
| skim_variable | year | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|
| life_exp | 1962 | 0 | 1 | 54.04 | 11.96 | 32.00 | 43.76 | 52.10 | 65.43 | 73.68 | ▃▇▃▅▆ |
| life_exp | 2007 | 0 | 1 | 67.79 | 11.28 | 39.61 | 59.80 | 71.76 | 76.18 | 82.60 | ▂▂▃▇▇ |
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_histogram(bins = 11, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
# panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp, y = after_stat(count/sum(count)))) +
geom_histogram(bins = 11, fill = "#440154", alpha = 0.9) +
theme_nath() +
scale_y_continuous(labels = scales::percent) +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
# panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
p1 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_histogram(bins = 11, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
x = NULL,
y = NULL,
fill = NULL) +
# scale_y_continuous(limits = c(0, 50)) +
theme(panel.grid.major.x = element_blank(),
# panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
p2 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 0.7, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
#axis.text.y=element_blank(),
legend.position = "none")
p1 + p2
patchwork::plot_annotation(title = 'Distribuição da expectativa de vida dos países, ano de 2007') ## $title
## [1] "Distribuição da expectativa de vida dos países, ano de 2007"
##
## $subtitle
## list()
## attr(,"class")
## [1] "waiver"
##
## $caption
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_levels
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_prefix
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_suffix
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_sep
## list()
## attr(,"class")
## [1] "waiver"
##
## $theme
## list()
## attr(,"class")
## [1] "waiver"
##
## attr(,"class")
## [1] "plot_annotation"p1 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_histogram(bins = 11, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
x = NULL,
y = NULL,
fill = NULL) +
# scale_y_continuous(limits = c(0, 50)) +
theme(panel.grid.major.x = element_blank(),
# panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
p2 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 0.7, color = "#21918c", fill = "#21918c", alpha = 0.9) +
geom_text(aes(x=50, y = 0.025, label = "Soma da área \n igual a 1"),
linetype="dashed", color = "#21918c") +
theme_nath() +
labs(title = "",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
#axis.text.y=element_blank(),
legend.position = "none")
p1 + p2
patchwork::plot_annotation(title = 'Distribuição da expectativa de vida dos países, ano de 2007') ## $title
## [1] "Distribuição da expectativa de vida dos países, ano de 2007"
##
## $subtitle
## list()
## attr(,"class")
## [1] "waiver"
##
## $caption
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_levels
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_prefix
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_suffix
## list()
## attr(,"class")
## [1] "waiver"
##
## $tag_sep
## list()
## attr(,"class")
## [1] "waiver"
##
## $theme
## list()
## attr(,"class")
## [1] "waiver"
##
## attr(,"class")
## [1] "plot_annotation"p1 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_histogram(bins = 4, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
x = NULL,
y = "contagem",
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
p2 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_histogram(bins = 12, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
p3 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_histogram(bins = 25, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
p1 + p2 + p3 +
patchwork::plot_annotation(title = 'Histogramas com bins = 4, 12 e 25') 
p1 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1.5, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
x = NULL,
y = "densidade",
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
p2 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 0.6, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
p3 <- gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 0.3, fill = "#440154", alpha = 0.9) +
theme_nath() +
labs(title = "",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
p1 + p2 + p3 +
patchwork::plot_annotation(title = 'Densidades com ajuste bandwidth = 1.5, 0.7 e 0.4') 
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
# geom_vline(aes(xintercept=mean(life_exp)), linetype="solid", color = "#21918c")+
# geom_text(aes(x=mean(life_exp)-3, y = 0.04, label = paste("média =", round(mean(life_exp),0))),
# linetype="dashed", color = "#21918c") +
# geom_vline(aes(xintercept=mean(life_exp) - sd(life_exp)), linetype="dashed")+
# geom_vline(aes(xintercept=mean(life_exp) + sd(life_exp)), linetype="dashed")+
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
geom_vline(aes(xintercept=mean(life_exp)), linetype="solid", color = "#21918c")+
geom_text(aes(x=mean(life_exp)-3, y = 0.04, label = paste("média =", round(mean(life_exp),0))),
linetype="dashed", color = "#21918c") +
# geom_vline(aes(xintercept=mean(life_exp) - sd(life_exp)), linetype="dashed")+
# geom_vline(aes(xintercept=mean(life_exp) + sd(life_exp)), linetype="dashed")+
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
geom_vline(aes(xintercept=mean(life_exp)), linetype="solid", color = "#21918c")+
geom_text(aes(x=mean(life_exp)-3, y = 0.04, label = paste("média =", round(mean(life_exp),0))),
linetype="dashed", color = "#21918c") +
geom_vline(aes(xintercept=mean(life_exp) - sd(life_exp)), linetype="dashed", color = "#31688e")+
geom_text(aes(x=mean(life_exp)- sd(life_exp)-1, y = 0.04,
label = round(round(mean(life_exp),0) - sd(life_exp),0)),
linetype="dashed", color = "#31688e") +
geom_vline(aes(xintercept=mean(life_exp) + sd(life_exp)), linetype="dashed", color = "#31688e")+
geom_text(aes(x=mean(life_exp)+ sd(life_exp)+1, y = 0.04,
label = round(mean(life_exp) + sd(life_exp),0)),
linetype="dashed", color = "#31688e") +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
geom_vline(aes(xintercept=mean(life_exp)), linetype="solid", color = "#21918c")+
geom_text(aes(x=mean(life_exp)-3, y = 0.04, label = paste("média =", round(mean(life_exp),0))),
linetype="dashed", color = "#21918c") +
geom_vline(aes(xintercept=mean(life_exp) - sd(life_exp)), linetype="dashed", color = "#31688e")+
geom_text(aes(x=mean(life_exp)- sd(life_exp)-1, y = 0.04,
label = round(round(mean(life_exp),0) - sd(life_exp),0)),
linetype="dashed", color = "#31688e") +
geom_vline(aes(xintercept=mean(life_exp) + sd(life_exp)), linetype="dashed", color = "#31688e")+
geom_text(aes(x=mean(life_exp)+ sd(life_exp)+1, y = 0.04,
label = round(mean(life_exp) + sd(life_exp),0)),
linetype="dashed", color = "#31688e") +
geom_vline(aes(xintercept=min(life_exp)), linetype="dotted", color = "darkgrey")+
geom_text(aes(x=min(life_exp)+1, y = 0.043,
label = round(min(life_exp),0)),
linetype="dashed", color = "darkgrey") +
geom_vline(aes(xintercept=max(life_exp)), linetype="dotted", color = "darkgrey")+
geom_text(aes(x=max(life_exp)-1, y = 0.043,
label = round(max(life_exp),0)),
linetype="dashed", color = "darkgrey") +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
geom_vline(aes(xintercept=median(life_exp)), linetype="solid", color = "#21918c")+
geom_text(aes(x=median(life_exp) - 4, y = 0.04,
label = paste("mediana = ", round(median(life_exp),0))),
linetype="dashed", color = "#21918c") +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
geom_vline(aes(xintercept=median(life_exp)), linetype="solid", color = "#21918c")+
geom_text(aes(x=median(life_exp) - 4, y = 0.04,
label = paste("mediana = ", round(median(life_exp),0))),
linetype="dashed", color = "#21918c") +
geom_vline(aes(xintercept=quantile(life_exp, 0.25)), linetype="dashed", color = "#31688e")+
geom_text(aes(x=quantile(life_exp, 0.25)-1, y = 0.04,
label = round(quantile(life_exp, 0.25),0)),
linetype="dashed", color = "#31688e") +
geom_vline(aes(xintercept=quantile(life_exp, 0.75)), linetype="dashed", color = "#31688e")+
geom_text(aes(x=quantile(life_exp, 0.75)+1, y = 0.04,
label = round(quantile(life_exp, 0.75),0)),
linetype="dashed", color = "#31688e") +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp)) +
geom_density(adjust = 1, fill = "#440154", alpha = 0.4) +
geom_vline(aes(xintercept=mean(life_exp)), linetype="solid", color = "#21918c")+
geom_text(aes(x=mean(life_exp)-3, y = 0.04, label = paste("média =", round(mean(life_exp),0))),
linetype="dashed", color = "#21918c") +
geom_vline(aes(xintercept=median(life_exp)), linetype="solid", color = "#fde725")+
geom_text(aes(x=median(life_exp) + 4, y = 0.03,
label = paste("mediana = ", round(median(life_exp),0))),
linetype="dashed", color = "#fde725") +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp, y =1)) +
# geom_violin(fill = "#440154", color = "#440154", alpha = 0.7) +
geom_violin(width=1, fill = "#440154", color = "#440154", alpha = 0.4) +
geom_boxplot(width=0.2, fill = "white", color="#440154", alpha=0.4) +
# geom_text(aes(x=median(life_exp) - 4, y = 0.04,
# label = paste("mediana = ", round(median(life_exp),0))),
# linetype="dashed", color = "#21918c") +
#
# geom_text(aes(x=quantile(life_exp, 0.25)-1, y = 0.04,
# label = round(quantile(life_exp, 0.25),0)),
# linetype="dashed", color = "#31688e") +
#
# geom_text(aes(x=quantile(life_exp, 0.75)+1, y = 0.04,
# label = "3º quartil" ),
# linetype="dashed", color = "#31688e") +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
axis.text.y=element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
legend.position = "none")
Continentes
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("1962", "1977", "2007")) %>%
mutate(year = forcats::fct_rev(as_factor(year))) %>%
ggplot(aes(x = life_exp, y = year)) +
ggridges::geom_density_ridges(fill = "#440154", alpha = 0.4, scale = 0.85) +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida dos países por ano",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
scale_x_continuous(limits = c(20, 90)) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
#axis.text.y=element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2007") %>%
ggplot(aes(x = life_exp, y = forcats::fct_rev(continent), color = continent, fill = continent)) +
ggridges::geom_density_ridges(alpha = 0.8) +
scale_fill_brewer(palette = "Set2") +
scale_color_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Distribuição da expectativa de vida por continente, ano de 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
scale_x_continuous(limits = c(20, 90)) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "1962") %>%
ggplot(aes(x = life_exp, y = forcats::fct_rev(continent), color = continent, fill = continent)) +
ggridges::geom_density_ridges(alpha = 0.8) +
scale_fill_brewer(palette = "Set2") +
scale_color_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Distribuição da expectativa de vida por continente, ano de 1962",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
scale_x_continuous(limits = c(20, 90)) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("1962", "2007")) %>%
ggplot(aes(x = life_exp, y = forcats::fct_rev(continent),
color = interaction(year,continent), fill = interaction(year,continent))) +
ggridges::geom_density_ridges(alpha = 0.4) +
scale_fill_manual(values = c("#66C2A5", "#388C72", "#FC8D62", "#FA4F0A",
"#8DA0CB","#4964A1", "#E78AC3","#D42C94",
"#A6D854", "#77A927")) +
scale_color_manual(values = c("#66C2A5", "#388C72", "#FC8D62", "#FA4F0A",
"#8DA0CB","#4964A1", "#E78AC3","#D42C94",
"#A6D854", "#77A927")) +
labs(title = "",
subtitle = "Distribuição da expectativa de vida por continente, 1962 e 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
scale_x_continuous(limits = c(20, 90)) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
## Region
gapminder_full %>%
filter(year == 2007) %>%
group_by(region) %>%
select(life_exp) %>%
skimr::skim()| Name | Piped data |
| Number of rows | 183 |
| Number of columns | 2 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | region |
Variable type: numeric
| skim_variable | region | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|
| life_exp | Australia and New Zealand | 0 | 1 | 80.72 | 0.73 | 80.20 | 80.46 | 80.72 | 80.98 | 81.24 | ▇▁▁▁▇ |
| life_exp | Caribbean | 0 | 1 | 72.63 | 5.32 | 60.92 | 70.42 | 73.03 | 76.53 | 78.75 | ▂▁▃▇▆ |
| life_exp | Central Africa | 0 | 1 | 65.53 | NA | 65.53 | 65.53 | 65.53 | 65.53 | 65.53 | ▁▁▇▁▁ |
| life_exp | Central America | 0 | 1 | 73.98 | 3.13 | 70.20 | 71.47 | 74.22 | 76.14 | 78.78 | ▇▂▁▇▂ |
| life_exp | Central Asia | 0 | 1 | 57.89 | 12.30 | 43.83 | 53.50 | 63.17 | 64.92 | 66.67 | ▃▁▁▁▇ |
| life_exp | Eastern Africa | 0 | 1 | 54.00 | 9.91 | 42.08 | 48.16 | 52.52 | 58.04 | 76.44 | ▇▇▂▁▂ |
| life_exp | Eastern Asia | 0 | 1 | 76.20 | 6.40 | 66.80 | 71.54 | 78.51 | 81.09 | 82.60 | ▅▂▁▅▇ |
| life_exp | Eastern Europe | 0 | 1 | 73.49 | 2.49 | 68.86 | 72.74 | 73.34 | 75.11 | 76.49 | ▂▁▇▂▅ |
| life_exp | Melanesia | 0 | 1 | 67.13 | 7.10 | 57.23 | 63.57 | 68.77 | 70.04 | 76.06 | ▃▃▁▇▃ |
| life_exp | Micronesia | 0 | 1 | 68.53 | NA | 68.53 | 68.53 | 68.53 | 68.53 | 68.53 | ▁▁▇▁▁ |
| life_exp | Middle Africa | 0 | 1 | 49.83 | 4.92 | 42.73 | 46.03 | 50.54 | 52.51 | 56.74 | ▇▃▇▃▇ |
| life_exp | Northern Africa | 0 | 1 | 70.21 | 5.83 | 58.56 | 71.21 | 71.82 | 73.52 | 73.95 | ▂▁▁▁▇ |
| life_exp | Northern America | 0 | 1 | 79.45 | 1.70 | 78.24 | 78.84 | 79.45 | 80.05 | 80.65 | ▇▁▁▁▇ |
| life_exp | Northern Europe | 0 | 1 | 78.77 | 3.19 | 71.37 | 78.75 | 79.37 | 80.37 | 81.76 | ▂▁▁▇▆ |
| life_exp | Polynesia | 0 | 1 | 72.94 | 1.34 | 71.45 | 72.38 | 73.31 | 73.68 | 74.06 | ▇▁▁▇▇ |
| life_exp | South America | 0 | 1 | 72.70 | 3.67 | 65.55 | 71.42 | 72.89 | 75.11 | 78.55 | ▃▂▇▇▃ |
| life_exp | South-Eastern Asia | 0 | 1 | 71.01 | 6.80 | 59.72 | 70.62 | 71.69 | 74.25 | 79.97 | ▅▁▇▅▅ |
| life_exp | Southeast Asia | 0 | 1 | 62.07 | NA | 62.07 | 62.07 | 62.07 | 62.07 | 62.07 | ▁▁▇▁▁ |
| life_exp | Southern Africa | 0 | 1 | 47.04 | 5.66 | 39.61 | 42.59 | 49.34 | 50.73 | 52.91 | ▃▃▁▃▇ |
| life_exp | Southern Asia | 0 | 1 | 66.93 | 3.28 | 63.78 | 64.54 | 65.55 | 69.09 | 72.40 | ▇▂▂▁▃ |
| life_exp | Southern Europe | 0 | 1 | 77.45 | 2.48 | 74.00 | 75.30 | 77.93 | 79.46 | 80.94 | ▇▅▅▅▅ |
| life_exp | Western Africa | 0 | 1 | 55.19 | 7.85 | 42.57 | 47.96 | 56.37 | 59.59 | 71.68 | ▆▁▇▂▁ |
| life_exp | Western Asia | 0 | 1 | 73.08 | 5.73 | 59.55 | 71.94 | 73.78 | 76.13 | 80.75 | ▂▁▂▇▅ |
| life_exp | Western Europe | 0 | 1 | 80.13 | 0.89 | 79.41 | 79.52 | 79.80 | 80.45 | 81.70 | ▇▁▂▁▂ |
| life_exp | NA | 0 | 1 | 69.46 | 2.76 | 65.47 | 67.17 | 69.03 | 71.97 | 72.96 | ▂▇▂▂▇ |
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year %in% c("1962", "1977", "2007")) %>%
filter(continent == "Ásia") %>%
mutate(year = forcats::fct_rev(as_factor(year))) %>%
ggplot(aes(x = life_exp, y = year)) +
ggridges::geom_density_ridges(alpha = 0.8, color = "#4964A1", fill = "#8DA0CB") +
# scale_fill_manual(values = c("#A6D854", "#77A927")) +
# scale_color_manual(values = c("#A6D854", "#77A927")) +
theme_nath() +
labs(title = "",
subtitle = "Distribuição da expectativa de vida da Ásia por ano",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
scale_x_continuous(limits = c(20, 90)) +
theme(panel.grid.major.x = element_blank(),
panel.grid.major = element_line(linetype = "dotted", colour = "lightgrey", size = 0.2),
#axis.text.y=element_blank(),
legend.position = "none")
boxplot
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == "2002") %>%
#filter(continent == "Oceania") %>%
#filter(country == "Australia") %>%
# group_by(year, country, continent) %>%
# summarise(
# life_exp = mean(life_exp, na.rm=T),
# fertility = mean(fertility, na.rm=T)
# ) %>%
# ungroup() %>%
#mutate(year = as_factor(year)) %>%
ggplot(aes(x = life_exp, y = continent, color = continent)) +
#ggplot(aes(x = continent, y = n, group = year, fill = year)) +
#geom_col(position = "dodge", colour = "white", size = 0.2, alpha = 0.8) +
#scale_y_continuous(labels = scales::comma, expand = c(0, 0)) +
#stat_summary(geom="point", fun.data = ~mean(.x,na.rm=T)) +
geom_boxplot() +
#geom_smooth(method = "glm") +
#facet_grid(. ~ country, scales = "free_x") +
#scale_fill_brewer(palette = "Set2") +
scale_color_brewer(palette = "Set2") +
# labs(title = "",
# subtitle = "Contagem de Países por Continente, de 1952 a 2002",
# caption = "Source: Gapminder.org",
# x = NULL,
# y = NULL,
# fill = NULL) +
theme_nath() +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
Rascunhos
Treemap
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == 2002) %>%
mutate(gdp_percap = pop * gdp_percap) %>%
group_by(year, country, continent) %>%
summarise(
life_exp = mean(life_exp, na.rm=T),
fertility = mean(fertility, na.rm=T),
gdp_percap = mean(gdp_percap, na.rm=T)
) %>%
ungroup() %>%
ggplot(aes(area = gdp_percap, fill = country, subgroup = continent, label = country)) +
treemapify::geom_treemap() +
treemapify::geom_treemap_subgroup_border(colour = "grey10") +
treemapify::geom_treemap_subgroup_text(fontface = "bold", colour = "#f0f0f0",
alpha = 0.7, place = "bottomleft") +
treemapify::geom_treemap_text(colour = "white", place = "centre", reflow = TRUE) +
#scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Country GDP by continent, 2002",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == 2002) %>%
mutate(gdp_percap = pop * gdp_percap) %>%
group_by(year, country, continent) %>%
summarise(
life_exp = mean(life_exp, na.rm=T),
fertility = mean(fertility, na.rm=T),
gdp_percap = mean(gdp_percap, na.rm=T)
) %>%
ungroup() %>%
ggplot(aes(area = gdp_percap, fill = continent, subgroup = continent, label = country)) +
treemapify::geom_treemap() +
treemapify::geom_treemap_subgroup_border(colour = "grey10") +
treemapify::geom_treemap_subgroup_text(fontface = "bold", colour = "#f0f0f0",
alpha = 0.7, place = "bottomleft") +
treemapify::geom_treemap_text(colour = "white", place = "centre", reflow = TRUE) +
scale_fill_brewer(palette = "Set2") +
labs(title = "",
subtitle = "Country GDP by continent, 2002",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme_nath() +
theme(legend.position = "none")
Lollipop + América
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == 2007) %>%
filter(continent == "América") %>%
#filter(region %in% c("Canada", "United States", "Dominican Republic", "Netherlands Antilles")) %>%
ggplot(aes(life_exp, fct_reorder(region, life_exp))) +
geom_point(color = "#FC8D62", alpha = 0.8) +
theme_nath() +
labs(title = "",
subtitle = "Expectativa de Vida dos países do continente Americano, 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")
gapminder_full %>%
filter(continent != "FSU") %>%
filter(year == 2002) %>%
filter(continent == "América") %>%
#filter(region %in% c("Canada", "United States", "Dominican Republic", "Netherlands Antilles")) %>%
ggplot(aes(life_exp, fct_reorder(region, life_exp))) +
geom_point(color = "#FC8D62", alpha = 0.8) +
geom_point(data = . %>% filter(country == "Brazil"), color = "mediumpurple4", alpha = 0.8) +
geom_text(data = . %>% filter(country == "Brazil"), aes(label = country),
color = "mediumpurple4", alpha = 0.8, vjust = -0.8, size = 4) +
theme_nath() +
labs(title = "",
subtitle = "Expectativa de Vida dos países do continente Americano, 2007",
caption = "Source: Gapminder.org",
x = NULL,
y = NULL,
fill = NULL) +
theme(panel.grid.major.x = element_blank(),
legend.position = "none")